Learner Reviews & Feedback for Structuring Machine Learning Projects by DeepLearning.AI
About the Course
Top reviews
YP
Jul 26, 2018
Very important and valuable intuitions about DNN training/optimization. It's full of really practical information while implementing my own models.DNN鞚 鞁れ牅 鞝侅毄頃犽晫 氚橂摐鞁 鞚错暣頃橁碃 鞝侅毄頃挫暭 頃 鞁れ鞝 雮挫毄霌る 甑劚霅 氅嬱 旖旍姢 鞛呺媹雼!
SV
Feb 20, 2019
This is the knowledge in which we will get from lots of experience only, but the andrew has shared in this course which might help us in future by saving a lot of time through this course experience
1401 - 1425 of 5,746 Reviews for Structuring Machine Learning Projects
By Kamal S
鈥Mar 24, 2018
This Course looked less important from the outside. Surprisingly gave me new ideas and cleared many misconceptions.
By Shaik A
鈥Feb 14, 2018
Very useful information. This course gave a chance to understand organize the neural networks and machine learning.
By Abin M A
鈥Feb 6, 2018
Very useful for beginners as this course explains many practical aspects techniques to approach real world problem.
By Karl H
鈥Feb 5, 2018
Very informative course. It would have been nice if there was an assignment on an application of transfer learning.
By Iman K
鈥Nov 21, 2017
best ML course. Hopefully we see more courses like this
. Maybe for specific problems or tools like tensorflow etc.
By Hamza A
鈥Aug 22, 2017
If you learn how to improve your machine learning applications efficiently, I highly recommend this course for you.
By claudia i r m
鈥Aug 28, 2022
A wonderful learning experience with great pedagogy and incredible concepts, applied through the labs and quizzes.
By kleber l
鈥Feb 16, 2021
This course although isn't code, it is useful, because, now I can guide my project towards a better path directed.
By Matthew N
鈥Feb 11, 2021
Andrew Ng is an awesome instructor on a very complex topic such as optimization and assessing models' performance.
By B V S A
鈥Aug 13, 2020
This is the most practical and well explained course on Deep learning implementation that I have ever come across.
By Dawood I
鈥Jun 9, 2020
Absolutely brilliant. What people learn after working on deep learning for years, Andrew taught us in this course.
By Manmohan K
鈥Jun 6, 2020
Gained good insight into the practical aspects of DL through this course and how to go about doing Error Analysis.
By Lakshya J
鈥Jun 3, 2020
Very practical and insightful course. I am sure these concepts will really help me when building my own ML systems
By Taiki O
鈥May 3, 2020
That was clear! However, some videos was ill-paced or I guess there was something wrong with the speed of videos.
By Hind A b
鈥Mar 7, 2020
very sightful course, i learned how to work on machine learning projects and how to analyse errors in development.
By Renato L R
鈥Jan 10, 2020
Very useful training that provides additional insights for a better plan and result's analysis of your ML projects
By Igor _
鈥Sep 13, 2019
This was the most useful course from the first three courses in this specialty; looking forward what will be next
By Rongyao W
鈥Aug 19, 2019
Great hands on experience with deep learning. It surely help a lot for building insight what deep learning can do.
By Jason D
鈥Aug 10, 2019
Good course to build up your knowledge on how to go about structuring machine learning projects in the real world.
By Hiren K
鈥Jul 30, 2019
Very interesting and informative course. Professor Ng was quite good at teaching complex phenomena in an easy way.
By Jonathan M
鈥Jul 26, 2019
Great course that shows you many different concepts and how you can approach different problems you may encounter.
By Paul H C
鈥Oct 9, 2018
This is so useful!!! I know now what to do when I blocked: keep iterating: start quickly and iterate until success
By David B
鈥Sep 9, 2018
Invaluable if you are implementing a project, which is, I guess, what we must do to fully understand the concepts.
By Leon G
鈥Jul 1, 2018
Abundant practical, industrial-level advice on ML projects and their improvements. Awesome course, awesome Andrew.
By Rodolfo C
鈥Apr 8, 2018
Good review of the machine learning mentality and how things can be simplified when using this kind of strategies.